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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
AIME
1997
Springer
14 years 22 days ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
SAC
2008
ACM
13 years 8 months ago
IELR(1): practical LR(1) parser tables for non-LR(1) grammars with conflict resolution
There has been a recent effort in the literature to reconsider grammar-dependent software development from an engineering point of view. As part of that effort, we examine a defic...
Joel E. Denny, Brian A. Malloy
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
13 years 10 months ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu
BMCBI
2010
142views more  BMCBI 2010»
13 years 8 months ago
Classification of protein sequences by means of irredundant patterns
Background: The classification of protein sequences using string algorithms provides valuable insights for protein function prediction. Several methods, based on a variety of diff...
Matteo Comin, Davide Verzotto